Maxime W. Lafarge

1.0k total citations
11 papers, 211 citations indexed

About

Maxime W. Lafarge is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Maxime W. Lafarge has authored 11 papers receiving a total of 211 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Artificial Intelligence and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Maxime W. Lafarge's work include Radiomics and Machine Learning in Medical Imaging (4 papers), AI in cancer detection (4 papers) and Medical Imaging Techniques and Applications (3 papers). Maxime W. Lafarge is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (4 papers), AI in cancer detection (4 papers) and Medical Imaging Techniques and Applications (3 papers). Maxime W. Lafarge collaborates with scholars based in Netherlands, Switzerland and United Kingdom. Maxime W. Lafarge's co-authors include Josien P. W. Pluim, Mitko Veta, Koen A. J. Eppenhof, Pim Moeskops, Shantanu Singh, Anne E. Carpenter, Juan Carlos Caicedo, Natalie D. ter Hoeve, P. J. van Diest and Nikolas Stathonikos and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Medical Imaging and The Journal of Pathology.

In The Last Decade

Maxime W. Lafarge

11 papers receiving 209 citations

Peers

Countries citing papers authored by Maxime W. Lafarge

Since Specialization

Citations

This map shows the geographic impact of Maxime W. Lafarge's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Maxime W. Lafarge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maxime W. Lafarge more than expected).

Fields of papers citing papers by Maxime W. Lafarge

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maxime W. Lafarge. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Maxime W. Lafarge. The network helps show where Maxime W. Lafarge may publish in the future.

Co-authorship network of co-authors of Maxime W. Lafarge

This figure shows the co-authorship network connecting the top 25 collaborators of Maxime W. Lafarge. A scholar is included among the top collaborators of Maxime W. Lafarge based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Maxime W. Lafarge. Maxime W. Lafarge is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

#	Work	Indexed citations
1	Image-based consensus molecular subtyping in rectal cancer biopsies and response to neoadjuvant chemoradiotherapy 2024 ·npj Precision Oncology ·Maxime W. Lafarge, Enric Domingo, Korsuk Sirinukunwattana, (unknown), Leslie Samuel, Graeme I. Murray, Susan D. Richman, Andrew Blake, David Sebag‐Montefiore, Simon Gollins, E. Klieser, Daniel Neureiter, Florian Huemer, Richard Greil, Philip D. Dunne, Philip Quirke, Lukas Weiß, Jens Rittscher, Tim Maughan, Viktor H. Koelzer	9
2	CohortFinder: an open-source tool for data-driven partitioning of digital pathology and imaging cohorts to yield robust machine-learning models 2024 ·SHILAP Revista de lepidopterología ·(unknown), (unknown), (unknown), John H. Shin, Yijiang Chen, (unknown), (unknown), (unknown), Maxime W. Lafarge, Viktor H. Koelzer, Laura Barisoni, Anant Madabhushi, Satish E. Viswanath, Andrew Janowczyk	2
3	Transcriptomics and proteomics reveal distinct biology for lymph node metastases and tumour deposits in colorectal cancer 2023 ·The Journal of Pathology ·Nelleke P.M. Brouwer, (unknown), (unknown), (unknown), Shannon van Vliet, (unknown), Pascal W.T.C. Jansen, Maxime W. Lafarge, Johannes H.W. de Wilt, Niek Hugen, Femke Simmer, Nigel B. Jamieson, Daniele V. F. Tauriello, (unknown), Michiel Vermeulen, Irıs D. Nagtegaal	15
4	Deep learning supported mitoses counting on whole slide images: A pilot study for validating breast cancer grading in the clinical workflow 2023 ·Journal of Pathology Informatics ·(unknown), Nikolas Stathonikos, Natalie D. ter Hoeve, Maxime W. Lafarge, Tri Q. Nguyen, P. J. van Diest, Mitko Veta	15
5	Learning Domain-Invariant Representations of Histological Images 2019 ·Frontiers in Medicine ·Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof, Mitko Veta	26
6	Progressively growing convolutional networks for end-to-end deformable image registration 2019 ·TU/e Research Portal ·Koen A. J. Eppenhof, Maxime W. Lafarge, Josien P. W. Pluim	9
7	Progressively Trained Convolutional Neural Networks for Deformable Image Registration 2019 ·IEEE Transactions on Medical Imaging ·Koen A. J. Eppenhof, Maxime W. Lafarge, Mitko Veta, Josien P. W. Pluim	49
8	Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning. 2019 ·PubMed ·Maxime W. Lafarge, Juan Carlos Caicedo, Anne E. Carpenter, Josien P. W. Pluim, Shantanu Singh, Mitko Veta	19
9	Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning 2018 ·Maxime W. Lafarge, (unknown), Anne E. Carpenter, Josien P. W. Pluim, Shantanu Singh, Mitko Veta	2
10	Deformable image registration using convolutional neural networks 2018 ·TU/e Research Portal ·Maxime W. Lafarge, Pim Moeskops, Mitko Veta, Josien P. W. Pluim, Koen A. J. Eppenhof	48
11	Multimodal angiographic assessment of cerebral arteriovenous malformations: a pilot study 2014 ·Journal of NeuroInterventional Surgery ·Raphaël Blanc, (unknown), Thomas Robert, Humain Baharvahdat, Maxime W. Lafarge, Julien Savatovsky, Jérôme Hodel, Gabriele Cicciò, Dorian Chauvet, Silvia Pistocchi, Bruno Bartolini, Hocine Redjem, Michel Piotin	17

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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